statistical quality design and control: contemporary concepts and methods

　　Emphasizing proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement, this text blends statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement.

　　Importance is placed on both the philosophical/conceptual underpinnings and the techniques and methods of SPC and DOE. The concepts and methods of Taguchi for quality design are combined with more traditional experimental design methods to promote the importance of viewing quality from an engineering design perspective.

Features

　　1.Features a blend of statistical process control (SPC) and design of experiments (DOE) concepts and methods for quality design and improvement.

　　2.Places particularly strong emphasis on proper methods for data collection, control chart construction and interpretation, and fault diagnosis for process improvement.

　　3.Provides careful explanations, using actual cases, of the relationship between quality intent through engineering design and its realization through manufacture.

　　4.Computer workshops and the associated software provided with the book allow readers to simulate processes and apply the methods presented to solve problems.

New To This Edition

　　1.Several new chapters:
　　Design and Analysis of Engineering Tolerances
　　Design and Analysis of Simple Comparative Experiments
　　Response Surface Methodology.

　　2.An updated perspective on the state of quality since 1990.

　　3. New case studies

　　4. Three new DOE computer workshops on factorial design, fractional factorial design, and response surface methodology.

　　5.40% new or revised homework problems

PART. I FUNDAMENTAL CONEPTS AND METHODS
Ch.1 Evolution of Quality Design and Control
Ch.2 Conceptual Framework for Quality: Design and Control
Ch.3 Statistical Methods and Probability Concepts for Data Characterization
Ch.4 Sampling Distributions and Statistical Hypothesis Testing
Ch.5 Conceptual Framework for Statistical Process Control

PART. II PROCESS CONTROL AND IMPROVEMENT
Ch.6 Shewhart Control Charts for Variable Data
Ch.7 Importance of Rational Sampling
Ch.8 Interpretation of X and R Control Charts: Use of Sampling Experiments
Ch.9 Some Control Chart Methods for Individual Measurements
Ch.10 Process Capability Assessment
Ch.11 The Design and Analysis of Tolerances
Ch.12 Statistical Thinking for Process Study: A Case Study
Ch.13 Shewhart Control Charts for Attribute Data
Ch.14 Attribute Control Chart Implementation for Process Improvement: Two Case Studies

PART. III PRODUCT/PROCESS DESIGN AND IMPROVEMENT
Ch.15 Conceptual Framework for Planned Experimentation
Ch.16 Design and Analysis of Simple Comparative Experiments
Ch.17 Design and Interpretation of 2k Factorial Experiments
Ch.18 Analysis of Two-Level Factorial Designs
Ch.19 Model Building for Design and Improvement Using Two-Level Factorial Designs
Ch.20 Two-Level Fractional Factorial Designs
Ch.21 Sequential and Iterative Nature of Experimentation
Ch.22 Robust Design Case Studies
Ch.23 Modeling of Response Surfaces and Response Optimization References and Further Readings

Appendix Tables